All Things Experience: Edition 33
Welcome back to All Things Experience, the newsletter that keeps you updated on the most recent happenings in the world of experience.?
This week, we’re bringing you original insights on the latest developments and use cases for AI in customer and employee experience.
For quick takeaways, check out our three questions with Medallia’s own Michael Mallett , Vice President, Product, CX Solutions Strategy, below.
Q: It’s no secret that adoption of AI has been uneven across industries. So, what have you been seeing — which verticals are leading the way and where is there untapped potential??
Michael: Data-rich industries are taking the lead in rapidly growing their use of AI, starting with technology companies because they’re either the creators of the models themselves or they’re providing different AI services to the organizations that they serve.?
The other industries that are doing well, similar to technology, have been leaning into automation for more effective operations. One example is manufacturing — they’re thinking about how they can improve productivity with AI in particular around predictive maintenance, demand forecasting, robotics. We’re seeing that financial services, with all the information that they have on their individual consumers and prospects, they’re better positioned to provide chat-based assistance, to understand what's happening over the phone to provide tailored real-time assistance or smarter follow-ups, and to proactively provide personalized recommendations and so forth using data-driven AI use cases.
The sectors that are behind are heavily regulated, risk-averse sectors, like government agencies and the public sector as well as healthcare represented untapped potential. As much as there's a very clear recognition of the value of artificial intelligence, machine learning, generative intelligence, and deep learning, there's equally a hesitancy of sending potentially sensitive data through these technologies at this time which limits the opportunity for direct experience management applications.
Q: What would you advise more risk-averse organizations to do when they get started with AI for CX and EX?
Michael: Don’t try to boil the ocean. Use a crawl-walk-run approach around what data you need, why, who will use it, and what impact it should have around any technology project?
Focus on one area of challenge or opportunity. Which customer-oriented journey or employee-oriented journey is currently too difficult or is being affected by a repeat issue? Where are there positive opportunities that the business is not yet seizing, but employees and customers really wish that you were?
How can you identify these moments? You can turn to digital behavior analytics and see users dropping off of an online process. Perhaps customers keep calling into the contact center about the same problem which can be identified through speech analytics. Or customers are repeatedly mentioning something in person to their financial advisor or their favorite retail associate, and that person is taking notes on the side and saying, “Gee, we're missing this opportunity.”
Focus on areas of pain or friction that if removed have the potential to deliver the greatest impact in the short term in order. That way you can show value in using new or enhancing existing AI - such as faster time to insight and action for an employee or expanded reach of customers acquired or served - to earn the right for expanded or even opportunistic use case coverage around growth and loyalty. Start with one to two key use cases before expanding to additional journeys, business units, and applications.
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Q: What are some clear use cases for AI and what are some areas where AI would be inappropriate for EX and CX?
Michael: The types of things that can and should be automated over time are repeat essential activities or general activities with known solutions such as following up on a past experience with helpful support or marketing messaging. AI can categorize, alert, and trigger workflows more consistently, with expanded coverage, and faster than any one individual or team could alone. And automating these kinds of actions from this intelligence is in the best interest of all, as doing so has the potential to help address customers’ and employees’ needs. This frees customers up to take care of other things, and it gives employees more time back in their day for more complex activities, innovation, and creative opportunities.?
Closing the loop, a foundational concept of experience management, is evolving as we speak because of this very technological movement. Nearly ? of Medallia users polled in November 2023 said they’re already deploying solutions for this very use case and ? more are likely to explore this in the near future. Other well established use cases such as searching for insights, generating reports based on native language, summarizing findings, and generating dynamic content are suitable for generative AI applications in the CX and EX space. And we shouldn’t forget about segmenting users, predicting outcomes, and recommending next best experiences which can be solved by our industry’s current machine learning and rules-based model approaches.
There are many other experience opportunities — such as highly sensitive, highly complex, or high empathy required situations — that artificial intelligence is not a fit for. In these cases, a personal touch or expert opinion needs to be provided. AI alone isn’t the answer because it’s not what all customers or employees to engage with in all cases, AI models are not yet trained sufficiently enough to navigate these scenarios without hallucinating or breaking with company policies,? it would be inappropriate and potentially a fiduciary and ethical riskwithout a human in the loop, or sometimes all of the above.
For example, in the case of employee experience management, it would be inappropriate to have Generative AI make hiring and firing decisions let alone even suggest it per EU AI Act which came into force August 1, 2024. Or for customer experience if a brand is at risk of losing a customer for life or in the healthcare sector a life-or-death matter is unfolding, no brand could justify AI should take the lead. And what about the touchpoints that led up to these sensitive journey end-states? Wouldn’t an AI-assisted but human-delivered touch be best to provide the best possible experience? In these instances, artificial intelligence will fall short of automatically handling situations or making recommendations for employees on exactly how to handle the situation. AI could be used to bring attention to an issue and even recommend what to do butit should be handed off to a human employee.?
The best, most meaningful and engaging experiences going forward will be creates as a result of artificial and human intelligence working together.?
Quick Hits | Notable News & Notes
Before you go, here are a few more insights you might find interesting:
Thanks for reading, and we’ll see you in a couple of weeks!
- Madeline Buyers , Content Marketing & Social Media Senior Specialist at Medallia